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Evaluation analysis on industrial green total factor productivity and energy transition policy in resource-based region

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  • Yaozu Xue

Abstract

Based on the input-output panel data of industrial sectors of Shanxi Province, which is the only province-wide resource-based region in China, this paper uses the non-parametric DEA model and the Malmquist productivity index to construct the DEA-Malmquist model for evaluation analysis of the green total factor productivity (GTFP) and its decomposition value of the sub-sector, and then through fixed effect panel regression model studies the ways of energy transition of the SDG’s. The results show that the technological progress index has the greatest contribution to the growth of GTFP, while the scale efficiency index has the lowest contribution. And the amount of investment in environmental pollution control has a significant positive relationship with the GTFP of the three major polluting industries in Shanxi. Among them, investment in environmental pollution control has the greatest positive effect on the GTFP of light polluting industries characterized by high technology, high added value and low emissions; investment in environmental pollution control has the largest positive effect on the GTFP of heavy polluting industries with heavy chemical industry and pollution-intensive industries; investment in environmental pollution control has the weakest positive effect on the GTFP of the medium polluting industries that manufacture life service products and some heavy industrial products. Based on these results, the paper puts forward effective policy for the energy transition of resource-based regions.

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  • Yaozu Xue, 2022. "Evaluation analysis on industrial green total factor productivity and energy transition policy in resource-based region," Energy & Environment, , vol. 33(3), pages 419-434, May.
    • Handle: RePEc:sae:engenv:v:33:y:2022:i:3:p:419-434
    DOI: 10.1177/0958305X211005428
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    Cited by:

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    2. Ruomeng Zhou & Yunsheng Zhang, 2023. "Measurement of Urban Green Total Factor Productivity and Analysis of Its Temporal and Spatial Evolution in China," Sustainability, MDPI, vol. 15(12), pages 1-32, June.
    3. Xiaoli Hao & Yuhong Li & Shufang Wen & Lulu Zhang, 2024. "Assessing the impact of digitalization on environmental efficiency: Do population factors and institutional factors Matter?," Journal of Information Economics, Anser Press, vol. 2(1), pages 80-101, March.
    4. Razzaq, Asif & Sharif, Arshian & Yang, Xiaodong & Dogan, Eyup, 2024. "Influence mechanism of electricity price distortion on industrial green transformation: A spatial analysis of Chinese regions," Energy Economics, Elsevier, vol. 130(C).
    5. Fan, Min & Zhou, Yun & Lu, Zhixi & Gao, Sen, 2024. "Fintech's impact on green productivity in China: Role of fossil fuel energy structure, environmental regulations, government expenditure, and R&D investment," Resources Policy, Elsevier, vol. 91(C).
    6. Wei Qiu & Yinghua Li & Haitao Wu, 2023. "The role of direct financing on regional green development: inhibition or promotion?," Economic Change and Restructuring, Springer, vol. 56(5), pages 3665-3699, October.

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